Pattern recognition based analysis of arm EMG signals and classification with artificial neural networks

Thanks to improving technology human life is consistently becoming easier. In points which exceeds human abilities machines come into play and they overcomes they remedy the deficiencies of human. One of the disciplines which must be evaluated in this coverage is manufacturing artificial hand for defective human which can manage with EMG signals. In this paper we tried to classify EMG signals which is belong to hands and arms who are limbs that human frequently use in daily life. It is demanded from 8 different able-bodied subjects to execute 7 different hand movements and it is inferred that obtained EMG signals are which class via artificial neural networks. In classification operations significant result is obtained.